MITS: a mixed-initiative intelligent tutoring system for sudoku

  • Authors:

  • Allan Caine;Robin Cohen

  • Affiliations:

  • David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada;David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

  • Venue:
  • AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
  • Year:
  • 2006

  • Harmony search algorithm for solving Sudoku

    KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I

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Abstract

In this paper, we propose a model called MITS — Mixed Initiative Intelligent Tutoring System for Sudoku. Extrapolating from theory for tutoring in scholastic subjects, and tutoring in the game of chess, we develop a model for tutoring the game of Sudoku using a mixed-initiative paradigm. Moreover, our aim is to design a system which not only proposes moves to make but also gives advice on why a particular move ought to be made. We operate in a decision-theoretic framework that measures the benefits and costs of interacting with students who are learning the game. The tutor will take the initiative to interact when the student lacks knowledge and is making moves that have low utility. But it will also interact when the student takes the initiative to elicit further input on the game he or she is trying to play. We illustrate our graphic user interface prototype and take the reader through a sample session. As a result, we present a system that is useful not only to gain insight into how to tutor students about strategy games but also about how to support mixed-initiative interaction in tutorial settings.